Semester Project

Introduction

[Provide a brief overview of your research question. Explain why you’re interested in the topic, where you found your data and the objectives of your analysis.]

Part 1: Descriptive Statistics

Part 1 of your semester project should include:

1. Reading in your data
2. Preparing the data a. This could include filtering out missing, bad or unnecessary data
3. Summarizing the data a. Identify and summarize your response variable
   • Visual summaries using ggplot
   • Numerical summary tables
     2. Explore the explanatory variables (check for outliers)
     3. Visualize the relationship between a few explanatory variables and your response variable using ggplot

Data Import and Preparation

library(tidyverse)
library(mosaic)
library(rio)
library(ggplot2)

# Be sure to make this using ggplot()

Visualizations

[Use ggplot() to create presentation-worth graphs (histograms, scatterplots, bar charts, boxplots, etc). Include an overall visualization of your response variable and one or two exploratory graphs showing the relationship between explanatory variables and your response.]

# Create Visuals Here

Numerical Summaries

[Create numerical summaries (favstats(), prop.table() with row or column totals, etc.) of your response variable. Include a table of summary statistics broken out by your explanatory variable. Include a discussion of what you observe.]

# Create numerical summaries

Part 2: Statistical Inference

Perform at least 1 complete statistical inference appropriate to your data, including:

1. State your null and alternative hypotheses
2. Perform the appropriate statistical test
3. Create confidence intervals where appropriate
4. Check test requirements
5. Correct interpretation and conclusions

State Ho and Ha

Hypothesis Test

# Perform the appropriate test for the data selected

Confidence Interval (where appropriate)

Check Test Requirements

Conclusion